基于计算机视觉的墙地砖表面缺陷检测

Research on the surface defect detection of floor tile based on computer vision

提出了一种基于计算机视觉的墙地砖表面缺陷识别方法,利用改进的分块图像相减匹配和相关算法,对目标图像和模板图像进行分块处理,将对应子区域图像与数据库中相应模块图像进行相减匹配检测,利用相关系数来判断目标图像质量是否满足要求。实验结果表明使用本文方法能够准确地实现墙地砖表面缺陷检测,检测出墙地砖表面平均缺陷数目为4.5个,平均识别率达95.74%,优于直方图统计特征法和灰度共生矩阵法,具有实时、可靠、高效的特点,对墙地砖表面检测具有较大的实用价值。

The paper presents a method on the surface defect detection of floor tile based on computer vision. With an improved image subtraction matching and correlation algorithm, the target image and the template image are partitioned into blocks and processed, and then the sub-area of the target image is subtracted from the corresponding template image in the data base. Finally the correlation coefficient is used to determine whether the quality of the target image meets the requirements. Experimental results show that this method can accurately achieve the reliable and efficient surface defect detection of floor tile in real-time. This method can detect the 4. 5 average defect and the average recognition rate can reach 95. 74% ,which is better than histogram statistical characteristics and GLCM. So the method is of great practical value of the surface defect detection of floor tile.